{
 "cells": [
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2024-12-25T01:07:56.546651Z",
     "start_time": "2024-12-25T01:07:56.531653Z"
    }
   },
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n"
   ],
   "outputs": [],
   "execution_count": 1
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-25T01:07:56.562652Z",
     "start_time": "2024-12-25T01:07:56.548654Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 设置随机种子，以便结果可以复现\n",
    "np.random.seed(42)\n",
    "\n",
    "# 生成数据的回归问题，采用有监督的机器学习方法\n",
    "# X1：生成100个从0到2的随机值\n",
    "X1 = 2 * np.random.rand(100, 1)\n",
    "# X2：生成100个从0到3的随机值\n",
    "X2 = 3 * np.random.rand(100, 1)"
   ],
   "id": "f9b2ea05a5b7cdb7",
   "outputs": [],
   "execution_count": 2
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-25T01:07:56.578654Z",
     "start_time": "2024-12-25T01:07:56.563654Z"
    }
   },
   "cell_type": "code",
   "source": "X1",
   "id": "9621711d897509fd",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.74908024],\n",
       "       [1.90142861],\n",
       "       [1.46398788],\n",
       "       [1.19731697],\n",
       "       [0.31203728],\n",
       "       [0.31198904],\n",
       "       [0.11616722],\n",
       "       [1.73235229],\n",
       "       [1.20223002],\n",
       "       [1.41614516],\n",
       "       [0.04116899],\n",
       "       [1.9398197 ],\n",
       "       [1.66488528],\n",
       "       [0.42467822],\n",
       "       [0.36364993],\n",
       "       [0.36680902],\n",
       "       [0.60848449],\n",
       "       [1.04951286],\n",
       "       [0.86389004],\n",
       "       [0.58245828],\n",
       "       [1.22370579],\n",
       "       [0.27898772],\n",
       "       [0.5842893 ],\n",
       "       [0.73272369],\n",
       "       [0.91213997],\n",
       "       [1.57035192],\n",
       "       [0.39934756],\n",
       "       [1.02846888],\n",
       "       [1.18482914],\n",
       "       [0.09290083],\n",
       "       [1.2150897 ],\n",
       "       [0.34104825],\n",
       "       [0.13010319],\n",
       "       [1.89777107],\n",
       "       [1.93126407],\n",
       "       [1.6167947 ],\n",
       "       [0.60922754],\n",
       "       [0.19534423],\n",
       "       [1.36846605],\n",
       "       [0.88030499],\n",
       "       [0.24407647],\n",
       "       [0.99035382],\n",
       "       [0.06877704],\n",
       "       [1.8186408 ],\n",
       "       [0.51755996],\n",
       "       [1.32504457],\n",
       "       [0.62342215],\n",
       "       [1.04013604],\n",
       "       [1.09342056],\n",
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       "       [1.93916926],\n",
       "       [1.55026565],\n",
       "       [1.87899788],\n",
       "       [1.7896547 ],\n",
       "       [1.19579996],\n",
       "       [1.84374847],\n",
       "       [0.176985  ],\n",
       "       [0.39196572],\n",
       "       [0.09045458],\n",
       "       [0.65066066],\n",
       "       [0.77735458],\n",
       "       [0.54269806],\n",
       "       [1.65747502],\n",
       "       [0.71350665],\n",
       "       [0.56186902],\n",
       "       [1.08539217],\n",
       "       [0.28184845],\n",
       "       [1.60439396],\n",
       "       [0.14910129],\n",
       "       [1.97377387],\n",
       "       [1.54448954],\n",
       "       [0.39743136],\n",
       "       [0.01104423],\n",
       "       [1.63092286],\n",
       "       [1.41371469],\n",
       "       [1.45801434],\n",
       "       [1.54254069],\n",
       "       [0.1480893 ],\n",
       "       [0.71693146],\n",
       "       [0.23173812],\n",
       "       [1.72620685],\n",
       "       [1.24659625],\n",
       "       [0.66179605],\n",
       "       [0.1271167 ],\n",
       "       [0.62196464],\n",
       "       [0.65036664],\n",
       "       [1.45921236],\n",
       "       [1.27511494],\n",
       "       [1.77442549],\n",
       "       [0.94442985],\n",
       "       [0.23918849],\n",
       "       [1.42648957],\n",
       "       [1.5215701 ],\n",
       "       [1.1225544 ],\n",
       "       [1.54193436],\n",
       "       [0.98759119],\n",
       "       [1.04546566],\n",
       "       [0.85508204],\n",
       "       [0.05083825],\n",
       "       [0.21578285]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 3
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-25T01:07:56.594656Z",
     "start_time": "2024-12-25T01:07:56.583655Z"
    }
   },
   "cell_type": "code",
   "source": "X2",
   "id": "95c790553a7e1eaa",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.09428756],\n",
       "       [1.90923123],\n",
       "       [0.94306794],\n",
       "       [1.52571207],\n",
       "       [2.72269942],\n",
       "       [0.74787669],\n",
       "       [1.23114877],\n",
       "       [2.26665342],\n",
       "       [0.6863945 ],\n",
       "       [0.23093973],\n",
       "       [0.86925436],\n",
       "       [0.48366386],\n",
       "       [2.78909296],\n",
       "       [2.42436114],\n",
       "       [1.90021127],\n",
       "       [2.61438177],\n",
       "       [2.41101623],\n",
       "       [0.55971018],\n",
       "       [2.677677  ],\n",
       "       [1.61802673],\n",
       "       [2.42232047],\n",
       "       [2.6882739 ],\n",
       "       [0.95401042],\n",
       "       [0.33015577],\n",
       "       [0.68380549],\n",
       "       [1.28132337],\n",
       "       [2.4540443 ],\n",
       "       [2.58219175],\n",
       "       [0.02085639],\n",
       "       [1.53224191],\n",
       "       [1.25223301],\n",
       "       [0.66632343],\n",
       "       [0.3595961 ],\n",
       "       [1.01284551],\n",
       "       [2.82872911],\n",
       "       [0.9696088 ],\n",
       "       [1.55637187],\n",
       "       [2.10905688],\n",
       "       [1.09088881],\n",
       "       [2.91534625],\n",
       "       [2.88734188],\n",
       "       [0.75534689],\n",
       "       [1.49174552],\n",
       "       [0.90263493],\n",
       "       [0.85452148],\n",
       "       [0.11066084],\n",
       "       [1.828693  ],\n",
       "       [1.50803707],\n",
       "       [0.15443625],\n",
       "       [0.83593939],\n",
       "       [2.72479766],\n",
       "       [0.71868567],\n",
       "       [0.43468462],\n",
       "       [1.46835828],\n",
       "       [2.95695136],\n",
       "       [0.72616581],\n",
       "       [2.01640664],\n",
       "       [2.28485885],\n",
       "       [0.71291263],\n",
       "       [2.18464905],\n",
       "       [1.1033494 ],\n",
       "       [1.89691749],\n",
       "       [1.90058913],\n",
       "       [1.60732405],\n",
       "       [0.27086931],\n",
       "       [2.50590749],\n",
       "       [0.96234019],\n",
       "       [0.55955553],\n",
       "       [0.12232542],\n",
       "       [1.77267883],\n",
       "       [2.03269309],\n",
       "       [0.04976349],\n",
       "       [1.53627917],\n",
       "       [0.67948733],\n",
       "       [1.93551837],\n",
       "       [0.52309929],\n",
       "       [2.07281321],\n",
       "       [1.16020604],\n",
       "       [2.81018997],\n",
       "       [0.41256283],\n",
       "       [1.02319905],\n",
       "       [0.34042056],\n",
       "       [2.77408085],\n",
       "       [2.63201806],\n",
       "       [0.77382488],\n",
       "       [1.97995214],\n",
       "       [2.4516666 ],\n",
       "       [1.66560243],\n",
       "       [1.58895174],\n",
       "       [0.72555687],\n",
       "       [0.2793083 ],\n",
       "       [2.69164727],\n",
       "       [2.70125417],\n",
       "       [1.89930437],\n",
       "       [1.01708937],\n",
       "       [1.04762872],\n",
       "       [2.17786704],\n",
       "       [2.69133078],\n",
       "       [2.66125927],\n",
       "       [2.33962664]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 4
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-25T01:07:56.610657Z",
     "start_time": "2024-12-25T01:07:56.596655Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 生成目标变量y，表示真实的数据\n",
    "# 真实值由线性关系生成：y = 5 + 4*X1 + 3*X2，再加上一个随机误差\n",
    "y = 5 + 4 * X1 + 3 * X2 + np.random.randn(100, 1)\n",
    "\n",
    "# 为了计算截距项W0，在X矩阵的开头加上一列全为1的列\n",
    "# 这样X_b的第一列将用于存储截距项W0\n",
    "X_b = np.c_[np.ones((100, 1)), X1, X2]\n",
    "\n",
    "# 完整的特征矩阵X_b\n",
    "X_b"
   ],
   "id": "45e20dddd72edc86",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.        , 0.74908024, 0.09428756],\n",
       "       [1.        , 1.90142861, 1.90923123],\n",
       "       [1.        , 1.46398788, 0.94306794],\n",
       "       [1.        , 1.19731697, 1.52571207],\n",
       "       [1.        , 0.31203728, 2.72269942],\n",
       "       [1.        , 0.31198904, 0.74787669],\n",
       "       [1.        , 0.11616722, 1.23114877],\n",
       "       [1.        , 1.73235229, 2.26665342],\n",
       "       [1.        , 1.20223002, 0.6863945 ],\n",
       "       [1.        , 1.41614516, 0.23093973],\n",
       "       [1.        , 0.04116899, 0.86925436],\n",
       "       [1.        , 1.9398197 , 0.48366386],\n",
       "       [1.        , 1.66488528, 2.78909296],\n",
       "       [1.        , 0.42467822, 2.42436114],\n",
       "       [1.        , 0.36364993, 1.90021127],\n",
       "       [1.        , 0.36680902, 2.61438177],\n",
       "       [1.        , 0.60848449, 2.41101623],\n",
       "       [1.        , 1.04951286, 0.55971018],\n",
       "       [1.        , 0.86389004, 2.677677  ],\n",
       "       [1.        , 0.58245828, 1.61802673],\n",
       "       [1.        , 1.22370579, 2.42232047],\n",
       "       [1.        , 0.27898772, 2.6882739 ],\n",
       "       [1.        , 0.5842893 , 0.95401042],\n",
       "       [1.        , 0.73272369, 0.33015577],\n",
       "       [1.        , 0.91213997, 0.68380549],\n",
       "       [1.        , 1.57035192, 1.28132337],\n",
       "       [1.        , 0.39934756, 2.4540443 ],\n",
       "       [1.        , 1.02846888, 2.58219175],\n",
       "       [1.        , 1.18482914, 0.02085639],\n",
       "       [1.        , 0.09290083, 1.53224191],\n",
       "       [1.        , 1.2150897 , 1.25223301],\n",
       "       [1.        , 0.34104825, 0.66632343],\n",
       "       [1.        , 0.13010319, 0.3595961 ],\n",
       "       [1.        , 1.89777107, 1.01284551],\n",
       "       [1.        , 1.93126407, 2.82872911],\n",
       "       [1.        , 1.6167947 , 0.9696088 ],\n",
       "       [1.        , 0.60922754, 1.55637187],\n",
       "       [1.        , 0.19534423, 2.10905688],\n",
       "       [1.        , 1.36846605, 1.09088881],\n",
       "       [1.        , 0.88030499, 2.91534625],\n",
       "       [1.        , 0.24407647, 2.88734188],\n",
       "       [1.        , 0.99035382, 0.75534689],\n",
       "       [1.        , 0.06877704, 1.49174552],\n",
       "       [1.        , 1.8186408 , 0.90263493],\n",
       "       [1.        , 0.51755996, 0.85452148],\n",
       "       [1.        , 1.32504457, 0.11066084],\n",
       "       [1.        , 0.62342215, 1.828693  ],\n",
       "       [1.        , 1.04013604, 1.50803707],\n",
       "       [1.        , 1.09342056, 0.15443625],\n",
       "       [1.        , 0.36970891, 0.83593939],\n",
       "       [1.        , 1.93916926, 2.72479766],\n",
       "       [1.        , 1.55026565, 0.71868567],\n",
       "       [1.        , 1.87899788, 0.43468462],\n",
       "       [1.        , 1.7896547 , 1.46835828],\n",
       "       [1.        , 1.19579996, 2.95695136],\n",
       "       [1.        , 1.84374847, 0.72616581],\n",
       "       [1.        , 0.176985  , 2.01640664],\n",
       "       [1.        , 0.39196572, 2.28485885],\n",
       "       [1.        , 0.09045458, 0.71291263],\n",
       "       [1.        , 0.65066066, 2.18464905],\n",
       "       [1.        , 0.77735458, 1.1033494 ],\n",
       "       [1.        , 0.54269806, 1.89691749],\n",
       "       [1.        , 1.65747502, 1.90058913],\n",
       "       [1.        , 0.71350665, 1.60732405],\n",
       "       [1.        , 0.56186902, 0.27086931],\n",
       "       [1.        , 1.08539217, 2.50590749],\n",
       "       [1.        , 0.28184845, 0.96234019],\n",
       "       [1.        , 1.60439396, 0.55955553],\n",
       "       [1.        , 0.14910129, 0.12232542],\n",
       "       [1.        , 1.97377387, 1.77267883],\n",
       "       [1.        , 1.54448954, 2.03269309],\n",
       "       [1.        , 0.39743136, 0.04976349],\n",
       "       [1.        , 0.01104423, 1.53627917],\n",
       "       [1.        , 1.63092286, 0.67948733],\n",
       "       [1.        , 1.41371469, 1.93551837],\n",
       "       [1.        , 1.45801434, 0.52309929],\n",
       "       [1.        , 1.54254069, 2.07281321],\n",
       "       [1.        , 0.1480893 , 1.16020604],\n",
       "       [1.        , 0.71693146, 2.81018997],\n",
       "       [1.        , 0.23173812, 0.41256283],\n",
       "       [1.        , 1.72620685, 1.02319905],\n",
       "       [1.        , 1.24659625, 0.34042056],\n",
       "       [1.        , 0.66179605, 2.77408085],\n",
       "       [1.        , 0.1271167 , 2.63201806],\n",
       "       [1.        , 0.62196464, 0.77382488],\n",
       "       [1.        , 0.65036664, 1.97995214],\n",
       "       [1.        , 1.45921236, 2.4516666 ],\n",
       "       [1.        , 1.27511494, 1.66560243],\n",
       "       [1.        , 1.77442549, 1.58895174],\n",
       "       [1.        , 0.94442985, 0.72555687],\n",
       "       [1.        , 0.23918849, 0.2793083 ],\n",
       "       [1.        , 1.42648957, 2.69164727],\n",
       "       [1.        , 1.5215701 , 2.70125417],\n",
       "       [1.        , 1.1225544 , 1.89930437],\n",
       "       [1.        , 1.54193436, 1.01708937],\n",
       "       [1.        , 0.98759119, 1.04762872],\n",
       "       [1.        , 1.04546566, 2.17786704],\n",
       "       [1.        , 0.85508204, 2.69133078],\n",
       "       [1.        , 0.05083825, 2.66125927],\n",
       "       [1.        , 0.21578285, 2.33962664]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 5
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "",
   "id": "212e9683d81e5def"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "$$\n",
    "\\theta = (X_b^T \\cdot X_b)^{-1} \\cdot X_b^T \\cdot y\n",
    "$$"
   ],
   "id": "1d5597c611af122"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-25T01:07:56.626654Z",
     "start_time": "2024-12-25T01:07:56.612657Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 使用解析解公式计算θ（权重参数）\n",
    "θ = np.linalg.inv(X_b.T.dot(X_b)).dot(X_b.T).dot(y)\n",
    "# 计算出的权重参数\n",
    "θ"
   ],
   "id": "1efd6fea366a3aa5",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[4.91061004],\n",
       "       [3.82913734],\n",
       "       [3.23977047]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 6
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-25T01:07:56.658657Z",
     "start_time": "2024-12-25T01:07:56.629655Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 使用模型进行预测\n",
    "# 创建一个新的特征矩阵X_new，包含两个待预测的样本\n",
    "X_new = np.array([[0, 0],\n",
    "                  [2, 3]])\n",
    "\n",
    "# 为了计算预测值，也为X_new添加一列全为1的列\n",
    "X_new_b = np.c_[np.ones((2, 1)), X_new]\n",
    "# 打印新特征矩阵X_new_b\n",
    "\n",
    "X_new_b\n"
   ],
   "id": "1123bd3fd1b4fa6a",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 0., 0.],\n",
       "       [1., 2., 3.]])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 7
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-25T01:07:56.673656Z",
     "start_time": "2024-12-25T01:07:56.661657Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 进行预测，y_predict = X_new_b * θ\n",
    "y_predict = X_new_b.dot(θ)\n",
    "# 打印预测结果\n",
    "y_predict"
   ],
   "id": "1c4c80ce5e7e0b34",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 4.91061004],\n",
       "       [22.28819613]])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 8
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-25T01:07:56.894653Z",
     "start_time": "2024-12-25T01:07:56.677656Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 使用matplotlib绘制图形，展示真实数据点和模型的预测结果\n",
    "# 绘制预测结果的红线\n",
    "plt.plot(X_new[:, 0], y_predict, 'r-')\n",
    "# 绘制真实数据点的蓝色散点\n",
    "plt.plot(X1, y, 'b.')\n",
    "# 设置坐标轴范围\n",
    "plt.axis([0, 2, 0, 25])\n",
    "# 显示图形\n",
    "plt.show()\n"
   ],
   "id": "36f18ccc43f59f80",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 9
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-25T01:07:57.082257Z",
     "start_time": "2024-12-25T01:07:56.896654Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "# 设置常数\n",
    "a = 1\n",
    "b = 1\n",
    "c = 0\n",
    "\n",
    "# 创建 x 和 y 的网格\n",
    "x = np.linspace(-5, 5, 100)\n",
    "y = np.linspace(-5, 5, 100)\n",
    "x, y = np.meshgrid(x, y)\n",
    "\n",
    "# 计算 z 值\n",
    "z = a * x + b * y + c\n",
    "\n",
    "# 绘制三维图形\n",
    "fig = plt.figure(figsize=(15, 6))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "ax.plot_surface(x, y, z, alpha=0.7, rstride=100, cstride=100)\n",
    "\n",
    "# 添加标签\n",
    "ax.set_xlabel('X-axis')\n",
    "ax.set_ylabel('Y-axis')\n",
    "ax.set_zlabel('Z-axis')\n",
    "ax.set_title('Planar function diagram')\n",
    "\n",
    "# 调整视角\n",
    "ax.view_init(elev=20, azim=-75)  # 这里设置了仰角为20度，方位角为-45度\n",
    "\n",
    "# 显示图形\n",
    "plt.show()\n"
   ],
   "id": "1260cc07db528075",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 10
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-25T01:07:57.097255Z",
     "start_time": "2024-12-25T01:07:57.084257Z"
    }
   },
   "cell_type": "code",
   "source": "",
   "id": "152909c664a8bf7e",
   "outputs": [],
   "execution_count": 10
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-25T01:07:57.113257Z",
     "start_time": "2024-12-25T01:07:57.099256Z"
    }
   },
   "cell_type": "code",
   "source": "",
   "id": "eb4797950c40417c",
   "outputs": [],
   "execution_count": 10
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-25T01:07:57.397258Z",
     "start_time": "2024-12-25T01:07:57.115258Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# 设置随机数种子以便于结果复现\n",
    "np.random.seed(42)\n",
    "\n",
    "# 模拟参数\n",
    "num_experiments = 1000  # 实验次数\n",
    "num_dice_rolls = 10     # 每次实验掷骰子的次数\n",
    "\n",
    "# 进行实验\n",
    "average_results = []\n",
    "\n",
    "for _ in range(num_experiments):\n",
    "    rolls = np.random.randint(1, 7, num_dice_rolls)  # 掷骰子，结果在1到6之间\n",
    "    # average = np.mean(rolls)                          # 计算平均值\n",
    "    average = np.sum(rolls)    #计算求和\n",
    "    \n",
    "    average_results.append(average)\n",
    "\n",
    "# 绘图\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.histplot(average_results, bins=30, kde=True, stat=\"density\", color='skyblue')\n",
    "plt.title('Distribution of Average Dice Rolls (10 Rolls per Experiment)')\n",
    "plt.xlabel('Average Value')\n",
    "plt.ylabel('Density')\n",
    "plt.axvline(x=3.5, color='red', linestyle='dashed', linewidth=2, label='Expected Mean (3.5)')\n",
    "plt.legend()\n",
    "plt.grid()\n",
    "plt.show()\n"
   ],
   "id": "dbbd7920a7755cf6",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 11
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-25T01:07:57.412261Z",
     "start_time": "2024-12-25T01:07:57.399260Z"
    }
   },
   "cell_type": "code",
   "source": "",
   "id": "4e091e4f45e9f2c3",
   "outputs": [],
   "execution_count": 11
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
